QRS complex detection using Empirical Mode Decomposition

In this paper, we present a new Empirical Mode Decomposition based algorithm for the purpose of QRS complex detection. This algorithm requires the following stages: a high-pass filter, signal Empirical Mode Decomposition, a nonlinear transform, an integration and finally, a low-pass filter is used....

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Bibliographic Details
Published inDigital signal processing Vol. 20; no. 4; pp. 1221 - 1228
Main Authors Hadj Slimane, Zine-Eddine, Naït-Ali, Amine
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.07.2010
Elsevier
Subjects
Algorithms
Computer Science
Computer Vision and Pattern Recognition
Decomposition
Digital signal processing
ECG signal
Empirical analysis
Empirical Modal Decomposition
Integration
Nonlinear transform
Nonlinearity
QRS detection
Transforms
QRS detection
Integration
ECG signal
Nonlinear transform
Empirical Modal Decomposition
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Summary:In this paper, we present a new Empirical Mode Decomposition based algorithm for the purpose of QRS complex detection. This algorithm requires the following stages: a high-pass filter, signal Empirical Mode Decomposition, a nonlinear transform, an integration and finally, a low-pass filter is used. In order to evaluate the proposed technique, the well known ECG MIT–BIH database has been used. Moreover it is compared to a reference technique, namely “Christov's” detection method. As it will be shown later, the proposed algorithm allows to achieve high detection performances, described by means both the sensitivity and the specificity parameters.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1051-2004
1095-4333
DOI:10.1016/j.dsp.2009.10.017